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PhoBERT: Pre-trained language models for Vietnamese (EMNLP-2020 Findings)
Question Answering in Vietnamese. In a nutshell, this project helps us answer a Question of a given Context in Vietnamese. [UPDATED] This won me a Top 2 Graduates of VietAI Advanced NLP 02.
End-to-end Multi-task Solutions for Aspect Category Sentiment Analysis (ACSA) on Vietnamese reviews, using PhoBERT as pretrained model
Sentiment-based classification for stock article title using PhoBert
Ensemble PhoBERT with FastText Embedding to improve performance on Vietnamese Sentiment Analysis tasks.
Phân loại văn bản Tiếng Việt sử dụng pretrained model - PhoBERT
Token classification using Phobert Models for Vietnamese
Quy Nhon AI Hackathon 2022 - Challenge 2: Review Analytics - Top 1 Solution
Text-level Aspect-Based Sentiment Analysis based on multi-task approach for Vietnamese reviews.
Extract vectors by setences and words with one layer or concat more layers
Customer Feedbacks :smile:
Vietnamese Fake News Detection Based on Hybrid Transfer Learning Model and TF-IDF
We build a subject recommendation system expected to improve students' learning quality at the University of Information Technology.
Pipeline for sentiment classification, use trainer of HuggingFace and use ONNX to export model
A simple Vietnamese Medical Chatbot Based
The 'Machine Learning' big project by Duc Tran Van, Minh Nguyen Tan, Trung Nguyen Hoang
vietnamese-text-classification
PyTorch deep learning model to detect toxic of Vietnamese sentences using Bert
Multi-task Aspect Category Sentiment Analysis for Vietnamese reviews
PhoBERT fine-tuned for sentiment analysis
This is the DEMO Vietnamese SBERT project that I put my heart into most clearly.
This project implements sentiment analysis using PhoBert, a pre-trained Vietnamese BERT model, on the UIT-VSFC dataset to classify the sentiment of Vietnamese text.
Simple fine-tunning and deploy PhoBERT
Project related to natural language processing to process similar documents
Applying BERT, PhoBERT, RoBERT models to natural language processing to detect official and unofficial news.
Fact-checking project classifying claims as SUPPORTED, REFUTED, or NEI. Uses ANN, DNN, RNN, CNN, Random Forest, PhoBERT, and Sentence Transformers.
image-captioning using ViT-PhoBERT model